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index.html_research_fellow
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<!DOCTYPE html>
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<title>Rafa Santana</title>
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<span class="d-block d-lg-none">Rafa Santana</span>
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<h1 class="mb-0">Rafa
<span class="text-primary">Santana</span>
</h1>
<div class="subheading mb-5">Physical Oceanographer
<div> <a href=""></a></a>
<a href="[email protected]">[email protected]</a>
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<div> <a href="For peer-reviewed publications:"></a>For peer-reviewed publications:</a>
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<div itemscope itemtype="https://schema.org/Person"><a itemprop="sameAs" content="https://orcid.org/0000-0002-3502-0031" href="https://orcid.org/0000-0002-3502-0031" target="orcid.widget" rel="me noopener noreferrer" style="vertical-align:top;"><img src="https://orcid.org/sites/default/files/images/orcid_16x16.png" style="width:1em;margin-right:.5em;" alt="ORCID iD icon">0000-0002-3502-0031</a></div>
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<p class="lead mb-5">I am a physical oceanographer with expertise in the dynamics of coastal, sub- and mesoscale ocean variability who focuses on improving the dynamical understanding of the oceans using a combination of observations, numerical modelling, and data assimilation. Currently, I am a research fellow at the <a href="https://www.auckland.ac.nz/en/science/about-the-faculty/department-of-physics.html/">The University of Auckland</a> working on the Scale-Aware Sea Ice Project <a href="https://sasip-climate.github.io/">(SASIP)</a>. At SASIP, my research focuses on understanding ocean-ice in Antarctic using the sea-ice model <a href="https://tc.copernicus.org/articles/10/1055/2016/">neXtSIM</a>. </p>
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I hold MSc and BSc degrees in Physical Oceanography from the Federal University of Bahia, Brazil
<p class="mb-2"></p> <b> Thesis Project in Video </b>
<p class="mb-0"></p>Sometimes a quick video is better than a long text. So check the video I have made for the <a href="https://www.canterbury.ac.nz/library/uc-library-news/2020/visualise-your-thesis-competition.html">2020 Visualise Your Thesis</a> competition in the local heat of my University. </p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/ONQqUUQMrPs" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<p class="mb-2"></p> <b> Current work motivation and methodology</b>
<p class="mb-0"></p>Understanding spatial and temporal variability in the ocean is crucial for successful management of the marine environment. This is particularly so in the New Zealand region, as it is one of the largest exclusive economic zones in the globe and has numerous social and industrial activities concentrated over the continental shelf (Zeldis et al., 2004). The East Auckland Current (EAuC) is a large scale boundary current adjacent to the New Zealand northeastern continental shelf. Despite its regional importance, the drivers of oscillations in the EAuC are not well understood. In this project, a data-assimilative numerical modelling study will be undertaken to evaluate and understand the dominant mechanisms that control the EAuC variability and its influence on the continental shelf circulation and water properties (e.g. temperature, salinity, and chlorophyll). To improve simulations over the New Zealand northeastern continental shelf, a methodology will be developed to assimilate observations from an autonomous ocean glider. This knowledge is of utmost importance for coastal management as physical processes can greatly influence marine ecosystem variability (Zeldis et al., 2004).</p>
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<p class="mb-2"></p> <b> PhD work</b>
<p class="mb-0"></p>The first chapter of my thesis is summarised in the article "Mesoscale and wind‑driven intra‑annual variability in the East Auckland Current" freely available at <a href="https://www.nature.com/articles/s41598-021-89222-3">https://www.nature.com/articles/s41598-021-89222-3</a> . It tells about a year in the life of the EAuC. There, we study mesoscale eddies (ocean cylinders of aprox. 100 km diameter) that dominated the circulation for a total of 260 days and the EAuC which was present for 110 days. Winds played an import role by generating variability shorter than 30 days in the velocity and temperature. </p>
<p><a href="https://www.nature.com/articles/s41598-021-89222-3">
<img width="1300" src="fig_maps.png" alt="" />
</a></p>
<p class="mb-2"></p> <b>Maps of Sea Surface Temperature (SST) spatial anomaly (coloured shade) (mean value in black), geostrophic (black arrows) and daily averaged in situ velocities (coloured arrows as in Fig. 1a) on (a) 11/5/2015, (b) 7/7/2015, (c) 26/8/2015, (d) 2/11/2015, (e) 6/1/2016, and (f) 18/4/2016 showing the mesoscale structures A1, C1, EAuC, A1, A2/C2, and C2, respectively.</b>
<p class="mb-0"></p></p>
<p class="mb-2"></p> <b> Modelling the East Auckland Current </b>
<p class="mb-0"></p>Surface and localised in situ observations are not enough to understand the full dynamics in the region. That's why we use numerical models that can provide daily 3D pictures of the oceans. In the figure below, we compare results from a model and observations from satellites and moored instruments. We can see that the model does a good job simulating the temperature structure. However, mesoscale eddy variability is not well represented. </p>
<img src="map-ssh-2015-2016-2.gif" alt="Left: Map of Sea Surface Height (AVISO = black countors; Model = shade), geostrophic currents (AVISO = blue arrows; Model = black arrows), and in situ velocities (red, cyan, blue and yellow arrows). Right: Cross-section of temperature (In situ = coloured contours; Model = shade). The cross-section location is shown by the grey line on the map." />
<p class="mb-2"></p> <b>Figure caption: Left - Map of Sea Surface Height (SSH) (AVISO = black countors; Model = shade), geostrophic currents (AVISO = blue arrows; Model = black arrows), and in situ velocities (red, cyan, blue and yellow arrows). Right - Cross-section of temperature (In situ = coloured contours; Model = shade). The cross-section location is shown by the grey line on the map. </b>
<p class="mb-0"></p></p>
<p class="mb-2"></p> <b> Data assimilation is needed </b>
<p class="mb-0"></p> Mesoscale eddies are generated by instabilities which are unpredictable. Therefore, we need to incorporate satellite-derived and in situ data into the model to constrain its solution closer to observed values. This process is called data assimilation and aims to solve the equation below, which considers both model error and representativeness errors present in the observations (combined into <b>K</b>).</p>
<p><a href="https://en.wikipedia.org/wiki/Data_assimilation">
<img src="oceanpredict-ecmwf.jpg" alt="" />
</a></p>
<p class="mb-0"></p> <b> Figure source: Joint ECMWF/OceanPredict workshop on Advances in Ocean Data Assimilation. </b>
<p class="mb-0"></p></p>
<p class="mb-2"></p> <b> Data Assimilation in the East Auckland Current </b>
<p class="mb-0"></p>Remotely-sensed and in situ observations were assimilated into the model (ROMS) using 4D-VAR. Sea surface height (SSH) and temperature (SST) and mooring temperature, salinity, velocity from stations M3, M4, and M5 were assimilated. The video below shows that the simulation on the right (ASFUVTS-h) better represents the mesoscale eddies in comparison to the freely evolving simulation on the left (Control-JRA55do). </p>
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<p class="mb-2"></p> <b>Figure caption: Model comparison: freely evolving simulation (Control-JRA55d0 - left) model with data assimilation of SSH, SST, velocity, temperature and salinity from moorings (M3-M5). Variables compared are Sea Surface Height (AVISO = black countors; Model = shade), geostrophic currents (AVISO = blue arrows; Model = black arrows), and in situ velocities (red, cyan, blue and yellow arrows). </b>
<!--
<img src="map-ssh-2015-2016-2.gif" alt="Left: Map of Sea Surface Height (AVISO = black countors; Model = shade), geostrophic currents (AVISO = blue arrows; Model = black arrows), and in situ velocities (red, cyan, blue and yellow arrows). Right: Cross-section of temperature (In situ = coloured contours; Model = shade). The cross-section location is shown by the grey line on the map." />
<p class="mb-2"></p> <b>Figure caption: Left - Map of Sea Surface Height (AVISO = black countors; Model = shade), geostrophic currents (AVISO = blue arrows; Model = black arrows), and in situ velocities (red, cyan, blue and yellow arrows). Right - Cross-section of temperature (In situ = coloured contours; Model = shade). The cross-section location is shown by the grey line on the map. </b>
<p class="mb-0"></p></p>
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<h3 class="mb-0">More coming soon ...</h3>
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